Cell Cycle

Kowalczyk et al. 2015 Cell cycle genes based on Kowalczyk et al. 2015, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665007/. Cell cycle is a main source of transcriptional variation between HSCs and cycling cells are more abundand in MPPs compared to LT- and ST-HSCs. 2708 genes, ~32% were significant cell cycle-dependent expression. Of those 92% were up-regulated in cycling versus noncycling cells. 8% were upregulated in noncycling versus cycling cells included some important genes for HSC quiescence which we should not filter out (Stat1, Stat3, Meis1, Pbx1, Klf6, Nfia). G1/S, S, G2, and G2/M phases defined based on functional annotations (The Reference Genome Group of the Gene Ontology Consortium 2009). G1 length varies widely among different cell types, is short specifically in self-renewing cells, and increases with differentiation.

Parameter settings

Import Seurat object

Import cell cycle genes from MSigDB using the GO term "cell cycle process" GO:0022402

Frequence of cell cycle genes in PC

Import cell cycle genes from Whitefield et al. 2002

Whitfield cell cycle genes

The input to any clustering method, such as linkage, needs to measure the dissimilarity of objects. The correlation measures similarity. So it needs to be transformed in a way such that 0 correlation is mapped to a large number, while 1 correlation is mapped to 0. This is done by computing the euclidean distance (dissimilarity) of 1-R correlation values.

Hierarchical Clustering
Agglomerative : An agglomerative approach begins with each observation in a distinct (singleton) cluster, and successively merges clusters together until a stopping criterion is satisfied.
Divisive : A divisive method begins with all patterns in a single cluster and performs splitting until a stopping criterion is met.

Correlate Whitfield cell cycle genes with single cell data

Seurat cell cycle genes

Cell cycle score

Regress cell cycle